This project addresses the fundamental question of how cells adjust their gene expression program in response to oxidative stress (OS) in order to ensure survival. OS, inflicted upon cells either as an intrinsic cost of aerobic metabolism or by extraneous conditions, is intimately linked to a variety of ageing-related diseases, including neurodegenerative disorders, inflammatory conditions, cancer, and the vascular complications of diabetes. OS is known to trigger a transcriptional program primarily geared toward recovery, but triggering cell death if the damage is irreparable. Whereas this program is relatively well characterized at the level of mRNA abundance, almost nothing is known about the coordination with posttranscriptional layers of gene expression control. This application explores the overarching hypothesis that gene expression in response to OS is shaped by an integrated multi-layered program that precisely coordinates transcriptional and posttranscriptional mechanisms to maximize survival. The aim is to describe these mechanisms quantitatively and validating them experimentally both by acquiring global gene expression datasets and by formalizing the connections in mathematical terms. Specifically, a novel model of integrated control is addressed that was inspired by preliminary studies which highlighted the limitations of predicting protein changes from changes in mRNA levels. Mathematical simulations suggested critical roles for control at the levels of mRNA and protein stability during stress that lead to te following propositions: a) Increased synthesis of stress-induced proteins coincides with increased oxidative damage and hence increased proteolytic clearance as a quality control mechanism. b) OS-triggered rapid translational shutdown leads to downregulation of OS-suppressed mRNAs but not proteins in order to liberate ribosome capacity for the efficient translation of OS-induced mRNAs. Within the realm of the proposed project, these predictions will be put to scrutiny by acquiring unique system-wide datasets that will feed into an iterative process of mathematical modeling and experimental validation to arrive at a comprehensive framework of stress-regulated gene expression. The studies also address the general applicability of the OS models for gene expression in response to other forms of environmental stress and to mammalian cells.